An Eye Detection System Based on Neural Autoassociators

Automatic eye tracking is a challenging task, with numerous applications in biometrics, security, intelligent human–computer interfaces, and driver’s sleepiness detection systems. Eye localization and extraction is, therefore, the first step to the solution of such problems. In this paper, we present a new method, based on neural autoassociators, to solve the problem of detecting eyes from a facial image. A subset of the AR Database, collecting individuals both with or without glasses and with open or closed eyes, has been used for experiments and benchmarking. Preliminary experimental results are very promising and demonstrate the efficiency of the proposed eye localization system.